CN114176532A - Clinical verification method for determining cfPWV parameters and application system thereof - Google Patents
Clinical verification method for determining cfPWV parameters and application system thereof Download PDFInfo
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Abstract
The invention discloses a clinical verification method for determining cfPWV parameters and an application system thereof, wherein the method comprises the following steps: obtaining a blood vessel elasticity cfPWV parameter calculated by a clinical staff based on a portable mobile terminal device, comparing gold standard cfPWV data measured by a compact analysis device with the blood vessel elasticity cfPWV parameter, obtaining a comparison result, determining the deviation degree of the cfPWV parameter and the gold standard cfPWV data according to the comparison result, and analyzing the consistency of the pulse wave conduction speed detection algorithm of the cfPWV measured by the compact analysis device and the portable mobile terminal device according to the deviation degree. Whether the blood vessel elasticity cfPWV parameter calculated by the portable mobile terminal equipment accords with the actual condition of a tester or not can be determined based on a reference sample of a gold standard, and whether the pulse wave velocity detection algorithm of the portable mobile terminal equipment is reasonable or not can be effectively judged so as to confirm whether the detection algorithm is effective for early screening of arteriosclerosis or not, so that the judgment accuracy and the experience of users are improved.
Description
Technical Field
The invention relates to the technical field of artificial intelligence detection and biological data verification, in particular to a clinical verification method and system for determining cfPWV parameters.
Background
Arteriosclerosis is the physiological basis of various cardiovascular diseases (including coronary heart disease, cerebral apoplexy and the like), and the continuous monitoring of arteriosclerosis has important significance for preventing and treating the cardiovascular diseases. The prevalence rate of peripheral arterial diseases in China is in a continuously rising stage, and research shows that the detection rate of carotid plaque of residents aged more than or equal to 40 years old in China is 13.9 percent; the prevalence rate of lower limb arterial diseases of natural population more than or equal to 35 years old in China is 6.6%, and therefore, it is presumed that about 4530 ten thousand patients with lower limb arterial diseases in China have the knowledge rate of only 1.38% shown by research, which indicates that the common people do not pay attention to arteriosclerosis. At present, the stiffness change of the elastic aorta can be reflected by measuring the carotid-femoral pulse wave velocity (cfPWV), the influence of vasoactive substances in blood is small, the result repeatability is good, and the method is a gold index for evaluating the stiffness of the artery accepted and recommended by the national and international hypertension guidelines. The european cardiology institute recommends that cfPWV is 10m/s as a defined threshold for evaluating the occurrence of functional changes of aorta, which is a boundary point of hypertension complicated with vascular damage, and the increase of the cfPWV value can reflect the risk of cardiovascular diseases (including coronary heart disease, stroke, etc.) in the future, so the current hypertension guideline uses cfPWV as an index for evaluating the elastic function abnormality of blood vessels, and is an early evaluation index for arteriosclerosis caused by hypertension. However, the conventional artery elastometry equipment is only used in medical places as a medical instrument, and is not suitable for daily detection of families or individuals due to large volume, high price and relatively complex operation of the equipment, so that the equipment has difficulty in long-term monitoring of chronic diseases and detection of non-disease people.
In the digital era, the mode of developing active health by utilizing the movable wearable device is opened and imperative, the intelligent terminal (wearable device) can acquire the electrocardio, pulse and other information of a user through the multifunctional sensor to calculate the pulse wave conduction velocity, and the index related to the artery function is measured and calculated by combining the characteristics of the pulse wave signal to evaluate the artery hardness, so that the daily monitoring of the artery function of people is satisfied, and no professional person or complicated operation is needed, compared with professional large-scale equipment, the intelligent terminal has the advantages of low price, convenience and practicability, and provides a new effective way for the artery hardness detection of low-cost large-scale people, and the prior art has no verification method for the cfPWV of the portable mobile terminal device, so that whether the pulse wave conduction velocity detection algorithm of the portable mobile terminal device is reasonable or not and whether the pulse wave conduction velocity detection algorithm is effective for early screening of arteriosclerosis or not can not be determined, the experience of the user is reduced.
Disclosure of Invention
Aiming at the problems shown above, the invention provides a clinical verification method and a clinical verification system for determining cfPWV parameters, which are used for solving the problems that whether a pulse wave velocity detection algorithm of a portable mobile terminal device is reasonable or not can not be determined so as to judge whether the algorithm is effective for early screening of arteriosclerosis or not, and the experience of users is reduced.
A clinical validation method of determining a cfPWV parameter, comprising the steps of:
acquiring blood vessel elasticity cfPWV parameters calculated by clinical personnel based on portable mobile terminal equipment;
comparing the golden standard cfPWV data measured by the Complior analysis equipment with the blood vessel elasticity cfPWV parameters to obtain a comparison result;
determining the degree of deviation between the cfPWV parameter and the gold-labeled cfPWV data according to the comparison result;
and analyzing the consistency of the measured cfPWV of the Complior analysis equipment and a pulse wave conduction velocity detection algorithm of the portable mobile terminal equipment according to the deviation degree.
Preferably, before obtaining the blood vessel elasticity cfPWV parameter calculated by the clinician based on the portable mobile terminal device, the method further comprises:
acquiring personal information of each clinical person, wherein the personal information comprises: height, weight, sex, age and medical history;
dividing all clinical staff into sample crowds of different age groups according to the age information of each clinical staff;
setting a health/sub-health/non-health label for each clinical person according to the medical history information of the clinical person;
after the setting is finished, each clinical staff is associated with the label and the clinical sample.
Preferably, the obtaining of the blood vessel elasticity cfPWV parameter calculated by the clinician based on the portable mobile terminal device includes:
performing neck-thigh distance measurement for each clinical staff for a target number of times to obtain a measurement result;
acquiring continuous target number of electrocardiogram and pulse wave detection results when each clinical person wears the portable mobile terminal equipment;
taking a median in the target number detection results, and calculating the neck-thigh pulse wave velocity of each clinical staff by using a pulse wave velocity detection algorithm of the portable mobile terminal equipment according to the median and the measurement results;
and confirming the neck femoral pulse wave conduction speed of each clinical person as the blood vessel elasticity cfPWV parameter of the clinical person.
Preferably, the comparing the golden standard cfPWV data measured by the compaor analysis device with the blood vessel elasticity cfPWV parameter to obtain the comparison result includes:
acquiring gold standard cfPWV data of target quantity measured by Complior analysis equipment for each clinical staff;
taking the median of the gold-labeled cfPWV data of each clinical staff with the target number as comparison gold-labeled cfPWV data;
and comparing the comparison gold-labeled cfPWV data of each clinical staff with the blood vessel elasticity cfPWV parameters of the clinical staff to obtain the comparison result.
Preferably, before comparing the golden-standard cfPWV data measured by the compliar analysis device with the blood vessel elasticity cfPWV parameter and obtaining a comparison result, the method further comprises:
selecting a first number of clinical staff from a preset number of clinical staff according to a preset condition;
constructing a test set by using a first number of clinical personnel, and constructing a training set by using the remaining second number of clinical personnel;
training the pulse wave velocity detection algorithm by using the training set;
and after the training is finished, testing the trained pulse wave velocity detection algorithm by using the test set, and verifying the effectiveness of the pulse wave velocity detection algorithm according to the test result.
Preferably, the determining the degree of deviation of the cfPWV parameter from the golden-labeled cfPWV data according to the comparison result includes:
calculating an absolute mean error between the cfPWV parameter and the gold-labeled cfPWV data, a mean error of a Bland-Altman method and a standard deviation of the Bland-Altman method according to the comparison result based on a preset evaluation index;
classifying the evaluation data of the cfPWV parameters and the gold-labeled cfPWV data by using a Bland-Altman method according to a mean error of the Bland-Altman method and a standard deviation of the Bland-Altman method by taking a preset cervical pulse wave conduction speed as a boundary to obtain a classification result;
calculating the sensitivity, specificity, macroscopic F1 value and accuracy of the classification result to obtain a calculation result;
and determining the degree of deviation between the cfPWV parameter and the gold-labeled cfPWV data according to the calculation result.
Preferably, analyzing the consistency of the measured cfPWV of the compact analysis device and the pulse wave velocity detection algorithm of the portable mobile terminal device according to the deviation degree comprises:
and confirming whether the sensitivity, the specificity, the macroscopic F1 value and the accuracy are in the preset range, if so, confirming that the cfPWV measured by the Complior analysis device is consistent with the pulse wave velocity detection algorithm of the portable mobile terminal device, otherwise, confirming that the cfPWV measured by the Complior analysis device is inconsistent with the pulse wave velocity detection algorithm of the portable mobile terminal device.
Preferably, after acquiring a target number of consecutive electrocardiographic and pulse wave detection results when each clinical person wears the portable mobile terminal device, the method further includes:
performing a shear wave transformation on each electrocardiogram and pulse wave detection image to determine high frequency coefficients and low frequency coefficients of each electrocardiogram and pulse wave detection image;
determining the waveform peak value and the waveform valley value of each electrocardiogram and pulse wave detection image according to the high-frequency coefficient and the low-frequency coefficient of each electrocardiogram and pulse wave detection image;
parsing each electrocardiogram and pulse wave detection image to determine a waveform sequence thereof;
adjusting the waveform sequence of the electrocardiogram and pulse wave detection images according to the waveform peak value and the waveform valley value of each electrocardiogram and pulse wave detection image;
extracting the sequence factor of the waveform sequence of each adjusted electrocardiogram and pulse wave detection image;
the sequence factors are evaluated for plausibility to determine the accuracy of each electrocardiogram and beat wave detection image.
A clinical validation system for determining a cfPWV parameter, the system comprising:
the acquisition module is used for acquiring blood vessel elasticity cfPWV parameters calculated by clinical staff based on the portable mobile terminal equipment;
the comparison module is used for comparing the golden standard cfPWV data measured by the Complior analysis equipment with the blood vessel elasticity cfPWV parameters to obtain a comparison result;
the determining module is used for determining the deviation degree of the cfPWV parameter and the golden-standard cfPWV data according to the comparison result;
and the analysis module is used for analyzing the consistency of the cfPWV measured by the compact analysis equipment and the pulse wave velocity detection algorithm of the portable mobile terminal equipment according to the deviation degree.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a workflow diagram of a clinical validation method of determining a cfPWV parameter provided by the present invention;
FIG. 2 is another workflow diagram of a clinical validation method of determining a cfPWV parameter provided by the present invention;
FIG. 3 is a population distribution chart of sample populations of different ages;
FIG. 4 is a personal information statistics chart for a clinical person;
FIG. 5 is yet another workflow diagram of a clinical validation method of determining a cfPWV parameter provided by the present invention;
FIG. 6 is a comparison result of cfPWV measurement value of the pulse wave velocity detection algorithm of the portable mobile terminal device and the golden label cfPWV data measured by the compiler analysis device;
FIG. 7 is a schematic diagram of the results of the analysis of the Bland-Altman consistency between the predicted value of the pulse wave velocity detection algorithm and the golden standard cfPWV data measured by the compiler analysis device;
fig. 8 is a schematic structural diagram of a clinical verification system for determining cfPWV parameters according to the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Arteriosclerosis is the physiological basis of various cardiovascular diseases (including coronary heart disease, cerebral apoplexy and the like), and the continuous monitoring of arteriosclerosis has important significance for preventing and treating the cardiovascular diseases. The prevalence rate of peripheral arterial diseases in China is in a continuously rising stage, and research shows that the detection rate of carotid plaque of residents aged more than or equal to 40 years old in China is 13.9 percent; the prevalence rate of lower limb arterial diseases of natural population more than or equal to 35 years old in China is 6.6%, and therefore, it is presumed that about 4530 ten thousand patients with lower limb arterial diseases in China have the knowledge rate of only 1.38% shown by research, which indicates that the common people do not pay attention to arteriosclerosis. At present, the stiffness change of the elastic aorta can be reflected by measuring the carotid-femoral pulse wave velocity (cfPWV), the influence of vasoactive substances in blood is small, the result repeatability is good, and the method is a gold index for evaluating the stiffness of the artery accepted and recommended by the national and international hypertension guidelines. The european cardiology institute recommends that cfPWV is 10m/s as a defined threshold for evaluating the occurrence of functional changes of aorta, which is a boundary point of hypertension complicated with vascular damage, and the increase of the cfPWV value can reflect the risk of cardiovascular diseases (including coronary heart disease, stroke, etc.) in the future, so the current hypertension guideline uses cfPWV as an index for evaluating the elastic function abnormality of blood vessels, and is an early evaluation index for arteriosclerosis caused by hypertension. However, the conventional artery elastometry equipment is only used in medical places as a medical instrument, and is not suitable for daily detection of families or individuals due to large volume, high price and relatively complex operation of the equipment, so that the equipment has difficulty in long-term monitoring of chronic diseases and detection of non-disease people.
In the digital era, the mode of developing active health by utilizing the movable wearable device is opened and imperative, the intelligent terminal (wearable device) can acquire the electrocardio, pulse and other information of a user through the multifunctional sensor to calculate the pulse wave conduction velocity, and the index related to the artery function is measured and calculated by combining the characteristics of the pulse wave signal to evaluate the artery hardness, so that the daily monitoring of the artery function of people is satisfied, and no professional person or complicated operation is needed, compared with professional large-scale equipment, the intelligent terminal has the advantages of low price, convenience and practicability, and provides a new effective way for the artery hardness detection of low-cost large-scale people, and the prior art has no verification method for the cfPWV of the portable mobile terminal device, so that whether the pulse wave conduction velocity detection algorithm of the portable mobile terminal device is reasonable or not and whether the pulse wave conduction velocity detection algorithm is effective for early screening of arteriosclerosis or not can not be determined, the experience of the user is reduced, and in order to solve the above problem, the present embodiment discloses a clinical verification method for determining cfPWV parameters.
A clinical validation method of determining a cfPWV parameter, as shown in fig. 1, comprising the steps of:
step S101, obtaining blood vessel elasticity cfPWV parameters calculated by clinical staff based on portable mobile terminal equipment;
step S102, comparing the golden standard cfPWV data measured by the Complior analysis equipment with the blood vessel elasticity cfPWV parameters to obtain a comparison result;
step S103, determining the deviation degree of the cfPWV parameter and the gold-labeled cfPWV data according to the comparison result;
and step S104, analyzing the consistency of the measured cfPWV of the compact analysis device and the pulse wave velocity detection algorithm of the portable mobile terminal device according to the deviation degree.
In this embodiment, after the pulse wave velocity detection algorithm of the portable mobile terminal device passes the verification, the cfPWV parameter measured by the portable mobile terminal device can be ensured to be a standard parameter, and the arterial hardness of the user can be determined according to the measured cfPWV parameter, so that the determination result is more accurate and objective to be in line with the reality.
The working principle of the technical scheme is as follows: obtaining a blood vessel elasticity cfPWV parameter calculated by a clinical staff based on a portable mobile terminal device, comparing gold standard cfPWV data measured by a compact analysis device with the blood vessel elasticity cfPWV parameter, obtaining a comparison result, determining the deviation degree of the cfPWV parameter and the gold standard cfPWV data according to the comparison result, and analyzing the consistency of the pulse wave conduction speed detection algorithm of the cfPWV measured by the compact analysis device and the portable mobile terminal device according to the deviation degree.
The beneficial effects of the above technical scheme are: by comparing the gold standard cfPWV data measured by the Complior analysis equipment with the blood vessel elasticity cfPWV parameter calculated by the portable mobile terminal equipment and determining the deviation degree of the two, the consistency of the blood vessel elasticity cfPWV measured by the Complior analysis equipment and the pulse wave conduction velocity detection algorithm of the portable mobile terminal equipment is analyzed, whether the blood vessel elasticity cfPWV parameter calculated by the portable mobile terminal equipment accords with the actual condition of a tester or not can be determined based on a reference sample of the gold standard, and further, whether the pulse wave conduction velocity detection algorithm of the portable mobile terminal equipment is reasonable or not can be effectively judged, so that whether the pulse wave conduction velocity detection algorithm is effective for early screening of arteriosclerosis or not is determined, and the judgment accuracy and the experience of users are improved.
In one embodiment, as shown in fig. 2, before acquiring the blood vessel elasticity cfPWV parameter calculated by the clinician based on the portable mobile terminal device, the method further comprises:
step S201, acquiring personal information of each clinical staff, wherein the personal information comprises: height, weight, sex, age and medical history;
step S202, dividing all clinical personnel into sample populations of different age groups according to the age information of each clinical personnel;
step S203, setting a health/sub-health/non-health label for each clinical staff according to the medical history information of the clinical staff;
step S204, after the setting is finished, associating each clinical staff with the label and the clinical sample thereof;
in the present embodiment, the divided sample populations of different ages are shown in fig. 3, and the individual information of the clinical staff is shown in fig. 4.
The beneficial effects of the above technical scheme are: the clinical parameters of the clinical samples can be effectively determined by classifying all the clinical personnel according to the personal information of each clinical personnel, so that the error of the detection cfPWV parameter of each clinical personnel can be determined to obtain accurate clinical data, and a foundation is laid for subsequent verification.
In one embodiment, as shown in fig. 5, the obtaining of the blood vessel elasticity cfPWV parameter calculated by the clinician based on the portable mobile terminal device includes:
s501, performing neck-thigh distance measurement for each clinical staff for a target number of times to obtain a measurement result;
s502, collecting continuous target number of electrocardiogram and pulse wave detection results when each clinical staff wears the portable mobile terminal equipment;
step S503, taking the median of the detection results of the target number, and calculating the neck and thigh pulse wave conduction velocity of each clinical staff according to the median and the measurement results by using a pulse wave conduction velocity detection algorithm of the portable mobile terminal equipment;
and step S504, confirming the neck femoral pulse wave conduction speed of each clinical person as the blood vessel elasticity cfPWV parameter of the clinical person.
The beneficial effects of the above technical scheme are: the objectivity of the detection result can be ensured to a certain extent by taking the median of the target number detection results, so that the detection result is more practical.
In one embodiment, the comparing the golden standard cfPWV data measured by the compliar analysis device with the blood vessel elasticity cfPWV parameter to obtain the comparison result includes:
acquiring gold standard cfPWV data of target quantity measured by Complior analysis equipment for each clinical staff;
taking the median of the gold-labeled cfPWV data of each clinical staff with the target number as comparison gold-labeled cfPWV data;
and comparing the comparison gold-labeled cfPWV data of each clinical staff with the blood vessel elasticity cfPWV parameters of the clinical staff to obtain the comparison result.
The beneficial effects of the above technical scheme are: the accuracy and objectivity of the comparison data can be ensured by taking the median as the comparison data, and the verification rationality of the pulse wave velocity detection algorithm is indirectly improved.
In one embodiment, before comparing the golden-standard cfPWV data measured by the compliar analysis device with the blood vessel elasticity cfPWV parameter and obtaining a comparison result, the method further comprises:
selecting a first number of clinical staff from a preset number of clinical staff according to a preset condition;
constructing a test set by using a first number of clinical personnel, and constructing a training set by using the remaining second number of clinical personnel;
training the pulse wave velocity detection algorithm by using the training set;
after the training is finished, testing the trained pulse wave velocity detection algorithm by using the test set, and verifying the effectiveness of the pulse wave velocity detection algorithm according to the test result;
in this embodiment, the ratio of the number of clinical staff: selecting 30 people at age <30, selecting 30 people at age 30-60, randomly selecting 90 people at age >60 and selecting 30 people as a test set, wherein 45 people are male and 45 people are female; the remaining second number of clinical personnel samples was used as a training set.
The beneficial effects of the above technical scheme are: the effectiveness of the pulse wave velocity detection algorithm can be ensured by training and testing the pulse wave velocity detection algorithm, the detection result is more practical, and a foundation is further laid for the follow-up verification of the pulse wave velocity detection algorithm.
In one embodiment, the determining a degree of deviation of the cfPWV parameter from gold-labeled cfPWV data according to the comparison result includes:
calculating an absolute mean error between the cfPWV parameter and the gold-labeled cfPWV data, a mean error of a Bland-Altman method and a standard deviation of the Bland-Altman method according to the comparison result based on a preset evaluation index;
classifying the evaluation data of the cfPWV parameters and the gold-labeled cfPWV data by using a Bland-Altman method according to a mean error of the Bland-Altman method and a standard deviation of the Bland-Altman method by taking a preset cervical pulse wave conduction speed as a boundary to obtain a classification result;
calculating the sensitivity, specificity, macroscopic F1 value and accuracy of the classification result to obtain a calculation result;
determining the degree of deviation between the cfPWV parameter and the gold-labeled cfPWV data according to the calculation result;
in this embodiment, the steps of calculating the sensitivity, specificity, macroscopic F1 value and accuracy of the classification result, the absolute mean error between the cfPWV parameter and the gold-labeled cfPWV data, the mean error of the Bland-Altman method, and the standard deviation of the Bland-Altman method are as follows:
assuming a total of N clinical staff, the result of the gold standard measured by the Complior analysis device of the ith subject is Xi, and the result of the pulse wave velocity detection algorithm is Yi, the absolute mean error (MAE) is defined as:
the mean error of the Bland-Altman method (BA _ ME) is defined as:
the standard deviation of the Bland-Altman method (BA _ STD) is defined as:
assume that the tested confusion matrix is:
the sensitivity is then defined as:
specificity is defined as:
the macroscopic F1 value is defined as:
the accuracy is defined as:
wherein 0 represents the class cfPWV <10m/s, and 1 represents the class cfPWV > 10 m/s;
the calculation results are shown in fig. 6.
The beneficial effects of the above technical scheme are: the gold-labeled cfPWV data detected by the two detection devices can be classified objectively and randomly by using a Bland-Altman method, the influence of interference factors is removed, the objectivity and the accuracy of the result are ensured, and further, the deviation degree of the two detection devices can be comprehensively evaluated from a plurality of parameters by calculating the specific values of a plurality of angles to determine the deviation degree of the two detection devices, so that the evaluation result is more practical and objective.
In one embodiment, analyzing consistency of the Complior analysis device measured cfPWV and the pulse wave velocity detection algorithm of the portable mobile terminal device according to the deviation degree comprises:
confirming whether the sensitivity, the specificity, the macroscopic F1 value and the accuracy are in a preset range, if so, confirming that the cfPWV measured by the Complior analysis device is consistent with a pulse wave velocity detection algorithm of the portable mobile terminal device, otherwise, confirming that the cfPWV measured by the Complior analysis device is inconsistent with the pulse wave velocity detection algorithm of the portable mobile terminal device;
the analysis result is shown in FIG. 7.
The beneficial effects of the above technical scheme are: whether the cfPWV measured by the compact analysis device is consistent with the pulse wave conduction velocity detection algorithm of the portable mobile terminal device can be accurately and quickly evaluated, and the evaluation efficiency and the evaluation accuracy are improved.
In one embodiment, after acquiring a target number of consecutive electrocardiographic and pulse wave detection results while each clinical person wears the portable mobile terminal device, the method further includes:
performing a shear wave transformation on each electrocardiogram and pulse wave detection image to determine high frequency coefficients and low frequency coefficients of each electrocardiogram and pulse wave detection image;
determining the waveform peak value and the waveform valley value of each electrocardiogram and pulse wave detection image according to the high-frequency coefficient and the low-frequency coefficient of each electrocardiogram and pulse wave detection image;
parsing each electrocardiogram and pulse wave detection image to determine a waveform sequence thereof;
adjusting the waveform sequence of the electrocardiogram and pulse wave detection images according to the waveform peak value and the waveform valley value of each electrocardiogram and pulse wave detection image;
extracting the sequence factor of the waveform sequence of each adjusted electrocardiogram and pulse wave detection image;
the sequence factors are evaluated for plausibility to determine the accuracy of each electrocardiogram and beat wave detection image.
The beneficial effects of the above technical scheme are: the rationality evaluation is carried out on the sequence factors of each electrocardiogram and pulse wave detection image to determine the accuracy of each electrocardiogram and pulse wave detection image, so that each electrocardiogram can be effectively evaluated to determine whether the electrocardiogram and pulse wave detection image is rational and practical, a foundation is laid for subsequent work, and the stability is improved.
The present embodiment also discloses a clinical verification system for measuring cfPWV parameters, as shown in fig. 8, the system includes:
an obtaining module 801, configured to obtain a blood vessel elasticity cfPWV parameter calculated by a clinical staff based on a portable mobile terminal device;
a comparison module 802, configured to compare the golden standard cfPWV data measured by the compiler analysis device with the blood vessel elasticity cfPWV parameter, and obtain a comparison result;
a determining module 803, configured to determine, according to the comparison result, a degree of deviation between the cfPWV parameter and the gold-labeled cfPWV data;
and the analysis module 804 is used for analyzing the consistency of the cfPWV measured by the compact analysis device and the pulse wave velocity detection algorithm of the portable mobile terminal device according to the deviation degree.
The working principle and the advantageous effects of the above technical solution have been explained in the method claims, and are not described herein again.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (9)
1. A clinical validation method for determining a cfPWV parameter, comprising the steps of:
acquiring blood vessel elasticity cfPWV parameters calculated by clinical personnel based on portable mobile terminal equipment;
comparing the golden standard cfPWV data measured by the Complior analysis equipment with the blood vessel elasticity cfPWV parameters to obtain a comparison result;
determining the degree of deviation between the cfPWV parameter and the gold-labeled cfPWV data according to the comparison result;
and analyzing the consistency of the measured cfPWV of the Complior analysis equipment and a pulse wave conduction velocity detection algorithm of the portable mobile terminal equipment according to the deviation degree.
2. A clinical verification method for determining cfPWV parameters according to claim 1, wherein before obtaining blood vessel elasticity cfPWV parameters calculated by a clinician based on a portable mobile terminal device, the method further comprises:
acquiring personal information of each clinical person, wherein the personal information comprises: height, weight, sex, age and medical history;
dividing all clinical staff into sample crowds of different age groups according to the age information of each clinical staff;
setting a health/sub-health/non-health label for each clinical person according to the medical history information of the clinical person;
after the setting is finished, each clinical staff is associated with the label and the clinical sample.
3. The clinical verification method for determining cfPWV parameters according to claim 1, wherein the obtaining of the blood vessel elasticity cfPWV parameters calculated by the clinician based on the portable mobile terminal device comprises:
performing neck-thigh distance measurement for each clinical staff for a target number of times to obtain a measurement result;
acquiring continuous target number of electrocardiogram and pulse wave detection results when each clinical person wears the portable mobile terminal equipment;
taking a median in the target number detection results, and calculating the neck-thigh pulse wave velocity of each clinical staff by using a pulse wave velocity detection algorithm of the portable mobile terminal equipment according to the median and the measurement results;
and confirming the neck femoral pulse wave conduction speed of each clinical person as the blood vessel elasticity cfPWV parameter of the clinical person.
4. A clinical validation method for determining cfPWV parameters according to claim 1, wherein the comparing golden-labeled cfPWV data measured by a compliar analysis device with the blood vessel elasticity cfPWV parameters to obtain a comparison result comprises:
acquiring gold standard cfPWV data of target quantity measured by Complior analysis equipment for each clinical staff;
taking the median of the gold-labeled cfPWV data of each clinical staff with the target number as comparison gold-labeled cfPWV data;
and comparing the comparison gold-labeled cfPWV data of each clinical staff with the blood vessel elasticity cfPWV parameters of the clinical staff to obtain the comparison result.
5. A clinical validation method for determining cfPWV parameters according to claim 1, wherein before comparing golden-labeled cfPWV data measured by a compliar analysis device with the blood vessel elasticity cfPWV parameters to obtain a comparison result, the method further comprises:
selecting a first number of clinical staff from a preset number of clinical staff according to a preset condition;
constructing a test set by using a first number of clinical personnel, and constructing a training set by using the remaining second number of clinical personnel;
training the pulse wave velocity detection algorithm by using the training set;
and after the training is finished, testing the trained pulse wave velocity detection algorithm by using the test set, and verifying the effectiveness of the pulse wave velocity detection algorithm according to the test result.
6. A clinical validation method for determining a cfPWV parameter according to claim 1, wherein the determining a degree of deviation of the cfPWV parameter from gold-labelled cfPWV data from the comparison result comprises:
calculating an absolute mean error between the cfPWV parameter and the gold-labeled cfPWV data, a mean error of a Bland-Altman method and a standard deviation of the Bland-Altman method according to the comparison result based on a preset evaluation index;
classifying the evaluation data of the cfPWV parameters and the gold-labeled cfPWV data by using a Bland-Altman method according to a mean error of the Bland-Altman method and a standard deviation of the Bland-Altman method by taking a preset cervical pulse wave conduction speed as a boundary to obtain a classification result;
calculating the sensitivity, specificity, macroscopic F1 value and accuracy of the classification result to obtain a calculation result;
and determining the degree of deviation between the cfPWV parameter and the gold-labeled cfPWV data according to the calculation result.
7. The clinical verification method for determining a cfPWV parameter of claim 6, wherein analyzing the Complior analysis device according to the deviation degree to measure the consistency of the cfPWV with the pulse wave velocity detection algorithm of the portable mobile terminal device comprises:
and confirming whether the sensitivity, the specificity, the macroscopic F1 value and the accuracy are in the preset range, if so, confirming that the cfPWV measured by the Complior analysis device is consistent with the pulse wave velocity detection algorithm of the portable mobile terminal device, otherwise, confirming that the cfPWV measured by the Complior analysis device is inconsistent with the pulse wave velocity detection algorithm of the portable mobile terminal device.
8. The clinical verification method of measuring cfPWV parameters according to claim 3, wherein after acquiring a target number of consecutive electrocardiographic and pulse wave detection results while each clinical person wears the portable mobile terminal device, the method further comprises:
performing a shear wave transformation on each electrocardiogram and pulse wave detection image to determine high frequency coefficients and low frequency coefficients of each electrocardiogram and pulse wave detection image;
determining the waveform peak value and the waveform valley value of each electrocardiogram and pulse wave detection image according to the high-frequency coefficient and the low-frequency coefficient of each electrocardiogram and pulse wave detection image;
parsing each electrocardiogram and pulse wave detection image to determine a waveform sequence thereof;
adjusting the waveform sequence of the electrocardiogram and pulse wave detection images according to the waveform peak value and the waveform valley value of each electrocardiogram and pulse wave detection image;
extracting the sequence factor of the waveform sequence of each adjusted electrocardiogram and pulse wave detection image;
the sequence factors are evaluated for plausibility to determine the accuracy of each electrocardiogram and beat wave detection image.
9. A clinical validation system for determining a cfPWV parameter, the system comprising:
the acquisition module is used for acquiring blood vessel elasticity cfPWV parameters calculated by clinical staff based on the portable mobile terminal equipment;
the comparison module is used for comparing the golden standard cfPWV data measured by the Complior analysis equipment with the blood vessel elasticity cfPWV parameters to obtain a comparison result;
the determining module is used for determining the deviation degree of the cfPWV parameter and the golden-standard cfPWV data according to the comparison result;
and the analysis module is used for analyzing the consistency of the cfPWV measured by the compact analysis equipment and the pulse wave velocity detection algorithm of the portable mobile terminal equipment according to the deviation degree.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116072305A (en) * | 2023-02-17 | 2023-05-05 | 北京中兴正远科技有限公司 | Clinical trial data acquisition system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20080044224A (en) * | 2008-04-30 | 2008-05-20 | (주)한별메디텍 | Method for noninvasive, continuous, and simultaneous measurement of blood pressure and arterial stiffness |
| CN104958064A (en) * | 2015-07-15 | 2015-10-07 | 四川宇峰科技发展有限公司 | Wearable arteriosclerosis detector and pulse wave velocity detecting method |
| CN110477900A (en) * | 2019-08-20 | 2019-11-22 | 赣州市立医院 | A kind of arteriosclerosis estimating method, apparatus and atherosclerosis detector |
| CN111000537A (en) * | 2019-12-24 | 2020-04-14 | 中国人民解放军陆军军医大学第一附属医院 | Method for correcting influence of age, sex and blood pressure on pulse wave propagation speed |
| CN111160153A (en) * | 2019-12-17 | 2020-05-15 | 华南理工大学 | Road surface drainage monitoring and evaluating method and system based on image processing |
| CN112274121A (en) * | 2020-10-28 | 2021-01-29 | 河北工业大学 | Noninvasive arteriosclerosis detection method and device based on multipath pulse waves |
| US20210030372A1 (en) * | 2018-04-23 | 2021-02-04 | Evonik Operations Gmbh | Methods to estimate the blood pressure and the arterial stiffness based on photoplethysmographic (ppg) signals |
-
2021
- 2021-12-31 CN CN202111662747.XA patent/CN114176532B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20080044224A (en) * | 2008-04-30 | 2008-05-20 | (주)한별메디텍 | Method for noninvasive, continuous, and simultaneous measurement of blood pressure and arterial stiffness |
| CN104958064A (en) * | 2015-07-15 | 2015-10-07 | 四川宇峰科技发展有限公司 | Wearable arteriosclerosis detector and pulse wave velocity detecting method |
| US20210030372A1 (en) * | 2018-04-23 | 2021-02-04 | Evonik Operations Gmbh | Methods to estimate the blood pressure and the arterial stiffness based on photoplethysmographic (ppg) signals |
| CN110477900A (en) * | 2019-08-20 | 2019-11-22 | 赣州市立医院 | A kind of arteriosclerosis estimating method, apparatus and atherosclerosis detector |
| CN111160153A (en) * | 2019-12-17 | 2020-05-15 | 华南理工大学 | Road surface drainage monitoring and evaluating method and system based on image processing |
| CN111000537A (en) * | 2019-12-24 | 2020-04-14 | 中国人民解放军陆军军医大学第一附属医院 | Method for correcting influence of age, sex and blood pressure on pulse wave propagation speed |
| CN112274121A (en) * | 2020-10-28 | 2021-01-29 | 河北工业大学 | Noninvasive arteriosclerosis detection method and device based on multipath pulse waves |
Non-Patent Citations (3)
| Title |
|---|
| 张絮洁;章亚平;殷兆芳;覃开蓉;梁夫友;: "基于上臂袖带振荡波估测动脉僵硬度的理论方法及临床实验", 中国医疗设备, no. 04 * |
| 牛婷立;杨学智;朱庆文;冯前进;刘亚明;王玉来;李庭凯;刘卓拉;司银楚;李海燕;杜红;马良宵;董晓英;赵兰萍;陈朝晖;刘振奇;牛欣;: "便携式四诊合参辅助诊疗仪的临床试验和临床评价研究", 北京中医药大学学报, no. 04 * |
| 邹欣瑾;何为;余传祥;毕喜飞;李松浓;: "动脉弹性功能参数检测与临床研究", 生物医学工程学杂志, no. 03 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116072305A (en) * | 2023-02-17 | 2023-05-05 | 北京中兴正远科技有限公司 | Clinical trial data acquisition system |
| CN116072305B (en) * | 2023-02-17 | 2023-09-29 | 北京中兴正远科技有限公司 | Clinical trial data acquisition system |
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